How are artificial neural networks different from normal computers?

0 Answers  

---

What can you do with an nn and what not?

0 Answers  

---

. Why are linearly separable problems of interest of neural network researchers? a) Because they are the only class of problem that network can solve successfully b) Because they are the only class of problem that Perceptron can solve successfully c) Because they are the only mathematical functions that are continue d) Because they are the only mathematical functions you can draw

1 Answers  

---

What is backprop?

0 Answers  

---

Which is true for neural networks? a) It has set of nodes and connections b) Each node computes it’s weighted input c) Node could be in excited state or non-excited state d) All of the mentioned

1 Answers  

---

How are nns related to statistical methods?

0 Answers  

---

What are combination, activation, error, and objective functions?

0 Answers  

---

What are the population, sample, training set, design set, validation set, and test set?

0 Answers  

---

 What is back propagation? a) It is another name given to the curvy function in the perceptron b) It is the transmission of error back through the network to adjust the inputs c) It is the transmission of error back through the network to allow weights to be adjusted so that the network can learn. d) None of the mentioned

1 Answers  

---

List some commercial practical applications of artificial neural networks?

0 Answers  

---

How many kinds of kohonen networks exist?

0 Answers  

---

The name for the function in question 16 is a) Step function b) Heaviside function c) Logistic function d) Perceptron function

1 Answers  

---